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The micro-Doppler (m-D) signatures can describe the refined motion characteristics of a marine target, which are helpful for target detection and recognition. Due to the complex sea clutter and m-D of marine target, traditional detection methods using time-frequency analysis have great limitations on accuracy and computational cost. In this paper, the micromotion signal model of sea surface target...
The micro-motion of a subject induces Doppler frequency modulations around the carrier frequency of the reflected sensor signals. Recently, it has been proved that sea clutter is significantly variable and sea surface subjects have their micro-motions influenced by the sea state. The micro-Doppler (m-D) signatures can describe the refined motion characteristics of sea surface target. The micromotion...
The micro-Doppler (m-D) signature of a sea surface target is employed for detection and modeled as a quadratic frequency modulated (QFM) signal. Furthermore, a novel long-time coherent integration method, i.e., Radon-fractional ambiguity function (RFRAF), is proposed to detect the m-D signal, which can compensate the range and Doppler migrations simultaneously. The m-D signal can be well matched and...
This paper introduces fractal-based variable step-size least mean square(FB-VSLMS) algorithm and proposes a model for radar target detection in sea clutter. FB-VSLMS algorithm deals with a specific class of fractal signals and except one of the step-size parameters requiring time-varying constraints, the constraints on the remaining parameters are time-invariant. And the step-size matrix is determined...
This paper introduces fractal-based variable step-size least mean square(FB-VSLMS) algorithm and proposes a model for radar target detection in sea clutter. FB-VSLMS algorithm deals with a specific class of fractal signals and except one parameter requiring time-varying constraints, the constraints on the remaining parameters are time-invariant. And the step-size matrix is determined completely with...
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